Knowledge Network System (KNS) by Evolutionary Collective Intelligence (ECI): Model, Algorithm and Applications

TL;DR

This paper introduces the Knowledge Network System (KNS), built using the Evolutionary Collective Intelligence (ECI) algorithm, integrating knowledge graph construction, recommendation, search, and social functions within a unified framework, demonstrated through the VISVA system.

Contribution

The paper presents the first integrated framework combining knowledge network construction, recommendation, search, and social functions using the ECI algorithm.

Findings

ECI effectively constructs the KNS with high-quality recommendations.

KNS integrates multiple functions in a unified framework.

VISVA demonstrates practical applications of KNS and ECI.

Abstract

Aiming at overcoming some inherent drawbacks and bottlenecks encountered by the conventional Knowledge, Recommendation, Search, and Social Systems, in this article we introduce the Knowledge Network System (KNS), a novel type of knowledge graph which is constructed by a new proposed algorithm, the Evolutionary Collective Intelligence (ECI) algorithm. The ECI, an agent-machine interactive algorithm, constructs the KNS by iteratively recommending interesting/matched samples/files to the agents, and meanwhile taking advantages of the collective intelligence of the agents. The ECI based KNS, to the best of our knowledge, is the first attempt in literature that integrates the functions of knowledge network construction, high-quality recommendation, new types of search and social in a same framework. Some real and potential applications of KNS and ECI are discussed, and a real system named VISVA is provided to demonstrate their efficacy. Some open problems for future works are also summarized in the end.